This relates generally to image processing and to techniques for improving the quality of images displayed in computed-based systems.
One of the tasks of the video post-processing pipeline is automatic color enhancement. In the hue, saturation, luminance (HSL) color space there are two different aspects that can be changed for color enhancement, hue adjustment and saturation adjustment. A typical hue adjustment example is the facial tone correction by moving the phase of the chrominance signal closer to the phase of the corresponding facial tones. While phase errors in the facial tone are reduced, the phase errors for other color components may be increased.
Color saturation may also be important because saturated colors are more appealing to the user's eye. To obtain a more vivid image, the basic approach of adjusting saturation of an image is by increasing the gain of the chrominance vector of the image. This operation is equivalent to multiplying the original chrominance vector by a saturation vector. Traditionally, color enhancers normally use a preset and fixed saturation factor, regardless of the input image characteristics. For less saturated video images, vivid effects can be obtained by applying a fixed saturation factor. However, for already saturated video images, over-saturation and loss of image details may result from over-saturation adjustment.
In addition, color banding may occur when directly increasing color saturation. Color banding occurs when a display is unable to render smooth color gradients and, instead, presents stripes or bands of colors, especially in very light or very dark areas.